CN103209642A - Sharing emotions on social networks - Google Patents

Abstract

Mental state information is collected from an individual through video capture or sensor information capture. The sensor information may be electrodermal activity, accelerometer readings, skin temperature, or other characteristics. The mental state information may be collected and analyzed over a period of time to determine the individual's mood. The individual may share their mental state information on a social network. The individual may be asked to choose whether to share their mental state information before sharing.

Description

share emotions on social networks

related application

This application claims priority to the following U.S. Provisional Patent Applications: "Sharing Affect Data Acrossa Social Network," Serial No. 61/414,451, filed November 17, 2010, filed February 2011 "Using Affect Within a Gaming Context," serial number 61/439,913, filed February 6, 61/447,089, "Affecting Videos," filed February 27, 2011 Recommendation and Visualization of Affect Responses to Videos," Serial No. 61/447,464, "Video Ranking Based on Affect," filed Feb. 28, 2011 Serial No. 61/467,209, filed March 24, "Baseline Face Analysis," and Serial No. 61/549,560, filed October 20, 2011, "Mental State Analysis of Voters of Voters)". Each of the above applications is hereby incorporated by reference in its entirety to the extent the jurisdiction allows.

technical field

This application generally concerns the analysis of psychological states and more specifically the sharing of emotional data on social networks.

Background technique

People spend a lot of time on the Internet, and much of that time includes viewing and interacting with web pages, including those of social networks. Assessment of mental states is key to understanding individuals and the way they respond to the world around them, and this world increasingly includes virtual worlds. Mental states cover a wide spectrum, from happy to sad, contented and worried, excited to calm, and many others. These psychological states are experienced in response to everyday events, such as frustration when stuck in traffic, boredom while waiting in line, impatience while waiting for coffee, and even when people interact with their computers and the Internet. Individuals can become quite perceptive and empathetic on the basis of assessing and understanding the mental states of others, but automatic assessment of mental states is more challenging. An empathetic person might sense another person's anxiety or happiness and respond accordingly. One's ability and means of perceiving the emotional states of others can be rather difficult to generalize and is often conveyed as having a "gut feeling".

Many mental states (such as confusion, concentration, and worry) can be identified to aid in the understanding of a person or group of people. People can collectively respond with fear or anxiety, such as after witnessing a disaster. Likewise, people can collectively respond with joyful enthusiasm, such as when their sports team wins. Certain facial expressions and head gestures can be used to identify the mental state a person is experiencing. The automation performed in assessing mental state based on facial expressions is limited. Certain physiological conditions can provide signs that inform a person's state of mind and have been used in crude ways in lie detector tests.

Contents of the invention

Analysis of people as they interact with the Internet and various media can be performed by collecting psychological states through evaluation of facial expressions, head posture, and physiological conditions. Then, some mental state analysis can be shared on a social network. A computer-implemented method for communicating a mental state is disclosed herein, the method comprising: collecting mental state data of an individual; analyzing the mental state data to generate mental state information; and sharing the mental state on a social network information. The method may further include choosing, by the individual, to share the mental state information. The method may further include presenting the mental state information to the individual prior to the selecting. The state of mind data can be collected over a period of time, and the state of mind information shared is a reflection of the individual's mood. Mood may include one of the group consisting of: frustrated, confused, disappointed, hesitant, cognitive overload, focused, busy, attentive, bored, exploring, confident, trusting, joyful, and satisfied. This sharing can include posting the mental state information to a social networking web page. The method may further include uploading the mental state information to a server. The method may further include distributing the mental state information on a computer network. The mental state data may include one of the group consisting of: physiological data, facial data, and actigraphy data. A webcam may be used to capture one or more of the facial data and the physiological data. The facial data may include information about one or more of the group consisting of facial expressions, action units, head gestures, smiles, frowns, squints, lowered eyebrows, raised eyebrows, and attention. The physiological data may include one or more of electrodermal activity, heart rate, heart rate variability, skin temperature, and respiration. The method may further include inferring a mental state based on the collected mental state data. The method may further include identifying similar mental states within the social network. These mental states may include one of the group consisting of: frustration, confusion, disappointment, hesitation, cognitive overload, focus, busyness, attention, boredom, exploration, confidence, trust, joy, and satisfaction. The method may further include communicating an image of the individual with the mental state information shared. The individual's image may be from a peak time of mental state activity. The image can include a video. The method may further include restricting posting of the mental state information to a subset of the social network. The method may further include sharing the aggregated mental state information on the social network. The mental state data may be collected when the individual interacts with a networked application. The web application may be one of the group consisting of: a landing page, a checkout page, a web page, a website, a video on the web application, a game on the web application, A trailer, a movie, a commercial, and a virtual world. The method can further include forwarding a reference to the networked application as part of the sharing of the mental state information. The reference can include a URL and a timestamp. The forwarding can include a profile image from the web-connected application. The forwarding can include a profile video from the networking application. The sharing can be part of a rating system for the networking application. The mental state data can be collected using a biosensor.

In some embodiments, a computer program product embodied in a computer readable medium for communicating a mental state may include: code for collecting mental state data of an individual; for analyzing the mental state data to generate a mental state information; a code for the individual to choose to share the mental state information; and a code for sharing the mental state information on a social network. In an embodiment, a system for sharing mental states may include: a memory for storing instructions; one or more processors attached to the memory, wherein the one or more processors are configured to : collecting mental state data of an individual; analyzing the mental state data to generate mental state information; receiving an instruction from the individual to choose to share the mental state information; and sharing the mental state information on a social network.

In some embodiments, a computer-implemented method for communicating a mental state includes: receiving mental state information of an individual; inferring the individual's mental state based on the received mental state information; Share these inferred mental states.

Various features, aspects and advantages of many embodiments will become more apparent from the following description.

Description of drawings

The following detailed description of certain embodiments can be read by reference to the following drawings, in which:

Figure 1 is an illustration of a webcam video screen.

FIG. 2 is an illustration of an analysis graph of sentiment data.

Figure 3 is a flow chart for sharing mental state information

Figure 4 is a flowchart of sharing on social networks

Figure 5 is an illustration of captured versus rendered facial responses.

Figure 6 is a diagram representing physiological analysis.

Figure 7 is a diagram of cardiac related sensing.

Figure 8 is a graphical representation of mental state analysis.

FIG. 9 is an illustration of a web page selected for sharing.

Figure 10 is an example social networking page content.

Figure 11 is a system diagram for sharing on social networks.

Detailed ways

This disclosure provides descriptions of various methods and systems for analyzing the psychological states of people as they interact with websites, networked applications, and/or other features on the Internet, the results of which are shared to social networks superior. In a society that is constantly connected via the Internet, social networking has increasingly become a part of everyday life. Communication is achieved through emails, postings, text messages, short messages, etc., but emotional communication is still a challenge. By conducting psychological state analysis and then communicating these state of mind on a social network, virtual communication becomes more relevant. Communication is not limited to explicit posts but allows for emotional communication. Mental states may include affective states and/or cognitive states. Examples of emotional states include happiness or sadness. Examples of cognitive states include concentration or confusion. Observing, capturing, and analyzing these psychological states can yield important information about people's responses well beyond current capabilities in web site type analysis.

One challenge addressed by the present disclosure is the collection and analysis of an individual's mental state to generate mental state information that may be shared on social networks. Mental state data can be collected from individuals while performing specific tasks or over longer periods of time. Mental state data may include physiological data from multiple sensors, facial data from a webcam, or actigraphy data. The mental state data can be analyzed to create mental state information. Mind state information may include mood, other mind states, mind state data or mind state information derived or inferred from mind state data. The individual's state of mind may include frustration, confusion, disappointment, hesitation, cognitive overload, focus, busyness, attention, boredom, exploration, confidence, trust, joy and satisfaction, or other emotional or cognitive states. Mental state information may relate to a particular stimulus (such as a reaction to a networked application) or may be a mood (which may relate to an extended period of time and may indicate, for example, a day's state of mind).

The individual may be given an opportunity to share their state of mind with others. If the individual chooses to share, the mental state can be shared on a social network. By posting mood information on social media or a social networking page, the mental state can be shared on the social network. The mental state shared may be an overall mood or may be a response to a particular stimulus. If the mental state is a response to a particular stimulus, a reference to that stimulus (eg, a web-connected application) can be shared. The reference may include a Uniform Reference Locator (URL) and/or a timestamp. An image of the individual corresponding to his mood may be published along with the mental state. Other individuals with similar mental states on the social network can be identified to the individual. And in some cases, the mental state of an individual's contacts on the social network can be aggregated and shared on the social network.

Figure 1 is an illustration of a webcam video screen. Window 100 may include a view and several buttons. The webcam view 110 may include a personal view. The webcam view 110 may be obtained by a webcam or some other camera device attached to the computer. The person's view may show video of the person's head, the entire person, or a certain part of the person. A person's head can be viewed where a face is shown, and facial expressions can be observed. Facial expressions may include facial movement and head gestures. Facial data can be observed, including facial movements and head poses for inferring mental states. Additionally, the observed data may include information about hand posture or body language and body movements, such as visible fidgeting. In various embodiments, these actions may be captured by cameras or by sensor readings. Facial data may include tilting the head sideways, leaning forward, smiling, frowning, and many other gestures or expressions. The facial data may include information such as facial expressions, action units, head poses, smiles, frowns, squints, lowered eyebrows, raised eyebrows, and attention. Webcam observations may include eye blink rates. For example, a decrease in blink rate may indicate significant engagement with what is being observed. Webcam observations can also capture physiological information. Observation can be accomplished through the webcam while the individual is using the computer to review their normal tasks. Observations can also be made while specific items are being viewed or interacted with, for example, a connected application, a video on a connected application, a game on a connected application, and a virtual world. In some embodiments, the webcam view 110 may become smaller, may become an icon, or may disappear while the individual is interacting with a web-connected application. In some embodiments, observations are made during the normal events of the day.

A record button 120 may be included to record the webcam view 110 . The video recording button 120 may be part of the individual's "selection" in the webcam view 110 in which permission is obtained to view mental state information and share this information. The use of the video button 120 can be explained by placing the mouse on the video button 120 . The record button 120 can be clicked to start recording. The recording button can be clicked again to stop the recording. In some embodiments, video recording may be done based on the sensed environment. Recording can start automatically as a result of viewing or interacting with a particular web-connected application. Recordings can end automatically at a specific point in time or when a networked application reaches its end point. One such example is a series of video trailers that may be viewed. The recording of this webcam view can start and end as each video trailer starts and ends. In an embodiment, rights may be granted for recording of webcam views in certain operating environments. Furthermore, the environment as well as the webcam view can be videotaped.

The graph button 130 can be used to display an analysis of the information collected while the network camera is recording. The graph button 130 can be moused over to explain the button's purpose. The graph button 130 can be clicked to display a graph as shown in FIG. 2 . The graph button 130 can be clicked prior to sharing the mental state information so that a person can determine whether he or she wants to share their mental state information with others. The sharing button 140 can be used to share the mental state information collected when the recording button 120 is clicked. The share button 140 may be part of an "opt-in" process for sharing mental state information with others. The share button 140 can be moused over to explain the button's purpose. The share button 140 can be clicked to share the mental state information with a person, a group of people, or a social network. By clicking the share button 140, the mental state information can be emailed, posted to Facebook( ^TM ), shared to Twitter( ^TM ), or other social networking sites. The sharing of mental state information may be a one-time event or may be continuous. Once shared, mental state information may be posted periodically to a social networking site. In this way, a person's mental state information can be disseminated to their social network. Sharing can also pass a reference to a networked application or pass the networked application itself. The reference to the networking application may be, for example, a web page link. Based on this sharing, the individual can communicate what was watched and its state of mind while watching it. The individual may further request responses elicited from the individual or from persons with whom he shares his state of mind.

FIG. 2 is an illustration of an analysis graph 210 of sentiment data. The analytics chart 210 may include "time" on the x-axis and "emotion" on the y-axis. A graph 230 may be shown depicting sentiment data over time. The time period shown may be the most recent time period when the individual was performing various tasks or a specific task, such as collecting mental state data while the individual was interacting with a networked application. Emotional data can be as simple as a head gesture indicating when an individual is leaning towards the screen. Leaning towards that screen may be an indicator of greater interest in what is being viewed on that screen. Emotional data can also be an action unit for mental state analysis. These action units may include raising one eyebrow, raising both eyebrows, smiling twitches, frowning, nostril dilating, squinting, and many other possibilities. These action units can be automatically detected by a computer system analyzing the video. Affective data may also be an assessment of a certain mental state. For example, a graph can show positive or negative responses. In some embodiments, colors may be used instead of graphs. For example, green can indicate a positive response, while red can indicate a negative one. Affective data can also be displayed graphically for more specific mental state assessments. For example, a single mental state can be plotted into the graph. Some mental states that can be mapped include frustration, confusion, disappointment, hesitation, cognitive overload, focus, busyness, attention, boredom, exploration, confidence, trust, joy, and satisfaction. In some embodiments, a smile trace may be displayed that provides a line for each occurrence of a smile. The lines of a smile can be darker and more pronounced as the smile is longer and more pronounced. Just as the graph button 130 can be selected from FIG. 1 , a back button 220 can be selected from the window shown in FIG. 2 . In various embodiments, the back button 220 can return the window to show a webcam view, previous networking applications, etc.

Fig. 3 is a flowchart of sharing mental state information. Process 300 may begin by collecting 310 mental state data of an individual. The mental state data may include collecting action units, collecting facial expressions, and the like. Physiological data can be obtained from video observations of a person. For example, heart rate, heart rate variability, locomotor activity, respiration, and perspiration can be observed from the video capture. Alternatively, in some embodiments, biosensors may be used to capture physiological information and may also be used to capture accelerometer readings. Permission may be required and obtained prior to collecting mental state data 310 . The mental state data may be collected by the client computer system.

The process 300 can continue analyzing the mental state data 320 to generate mental state information. While the mental state data may be raw data (eg, heart rate), the mental state information may include information derived from the raw data. The mental state information may include the mental state data. The mental state information may include valence and arousal. The mental state information may include the mental states experienced by the individual. Some embodiments may further include inferring a mental state based on the collected mental state data.

The process 300 can continue with uploading mental state information 330 to a server. The server may be remote from the user and may host data used by a social network, but in other embodiments the server may be separate from the social network's computer system and used for storage of mental state information, among other functions. In some cases, an image may be communicated 340 to the server along with the mental state information. The image may be of the individual when the mental state data was collected, and may represent the mental state information. In other embodiments, the image may be captured or identified in advance to represent a particular mental state. The process 300 can continue with presenting the mental state information 350 to the individual before opting to share. Some embodiments may allow the user to make selections prior to presentation. In some embodiments, the mental state data, the mental state information, or a subset of the mental state information may be presented to the individual. May not be present in some embodiments. The mental state information can be presented to the individual in various ways, such as a textual description of mood, an image obtained from or from the individual, a graph as shown in Figure 2 or Figure 8, or other methods that convey the mental state way of information.

The process 300 may continue with the individual choosing to share the mental state information 360 or mental state. The individual may choose to limit release 362 of the mental state information. The individual may choose to share all or a portion of the mental state data and mental state information. The individual may choose to share with one person, a group of people, or on a social network, such as limiting the release of the mental state information to a subset of the social network. In an embodiment, mental state information may be shared with others that the network may recommend. In some embodiments, a reference to a networked application can be forwarded 364 to the selected group or subgroup. In some embodiments, the retweeting is done by selecting a "like" type button on the web page. The reference may include information about videos, trailers, e-books, websites, movies, commercials, television shows, streaming video clips, video games, computer games, and the like. The reference may include a timestamp, page number, webpage URL, etc. to identify a portion of the reference. The retweet may include a Twitter ^(TM) message, text, SMS, etc. When forwarding 364 the reference, a URL or short URL may be included. The process 300 can continue with sharing mental state information 370 . This sharing may include transmitting data from the individual's client computer to a server that retains the mental state information. The share can include a web page link, a web application reference, or a web application. The mental state information may be communicated to the individual 380 from the server. Alternatively, there may be peer-to-peer sharing of mental state information from a first person to a second person. Some embodiments may include sharing the mental state information 382 on a social network. Mental states may be communicated via Facebook ^™ , LinkedIn ^™ , MySpace ^™ , Twitter ^™ , Google+ ^™ , or other social networking sites.

Figure 4 is a flowchart of sharing on social networks. The process 400 describes a computer-implemented method for sharing mental states and can represent activities from a server's point of view. The process 400 may begin by receiving mental state data 410 of an individual. The mental state information may be collected as described in process 300, or may be received from the client computer that collected the mental state information. In some embodiments, this mental state information 420 may be analyzed to extract further information, such as facial expressions, action units, head gestures, smiling, frowning, squinting, lowered eyebrows, raised eyebrows, or attention. A choice to share mental state information may be received 430 from the individual to indicate their desire to share the mental state information with others. The choice may be from a user selecting a button on a screen of a web-based application to opt-in to share mental state information.

The process 400 continues with inferring 440 the individual's mental state based on the received mental state information. These mental states that can be inferred include depression, confusion, disappointment, hesitation, cognitive overload, focus, busyness, attention, boredom, exploration, confidence, trust, joy, and satisfaction. In some embodiments, the collective mental state of a group of people may be inferred. The process 400 continues with sharing 450 the inferred mental states on a social network. Some embodiments may include identifying similar mental states 452 within the social network. The group of people that may be searched to identify similar mental states may vary according to the embodiment. Some embodiments can only search an individual's direct contact list, while other embodiments can search an extended contact list, such as contacts that include the individual's contacts, or expand several levels to the contacts of the contacts A more extended group of . In other embodiments, only a group that has been specifically created to share mental state information may be searched, while other embodiments may search outside the individual's extended network to help identify individuals who may be of interest to the individual and who may be potential new contact person.

Individuals may collect and publish their mental state information on a computer network 460 for various purposes. These mental states can be aggregated together and the combined mental state assessment can be published or disseminated to others. Network administrators can collect emotional data and mental state information. This data and/or information can be tagged to a website controlled by the network administrator, and thus the mental states can be associated with the networked application. Additionally, the aggregated responses can be used to assess the virus potential of a networked application, such as a video or game. This aggregation may take various forms in various embodiments, but examples may include creating aggregated moods of a person's contacts on a social network, creating aggregated mental state information for people who have watched a Percentage tabulation of specific populations by mental state, or any other method of summarizing mental state information. Process 400 may conclude with sharing aggregated mental state information 470 on a social network.

Figure 5 is an illustration of capturing a rendered facial reaction. In system 500, electronic display 510 may show a rendering 512 to a person 520 to collect facial data and/or other indications of mental state. A webcam 530 is used to capture one or more of the facial data and the physiological data. In various embodiments, the facial data may include information about facial expressions, action units, head gestures, smiles, frowns, squints, lowered eyebrows, raised eyebrows, and attention. The webcam 530 can capture video, audio, and/or still images of the person 520 . A webcam (as the term is used herein and in the claims) may be a video camera, still camera, thermal imager, CCD device, cell phone camera, stereo camera, depth camera, multiple web cameras used to show different views of the person 520 530 or any other type of image capture device that might allow the captured data to be used in an electronic system. The electronic display 510 may be any electronic display including, but not limited to, a computer monitor, laptop screen, netbook screen, tablet computer, cell phone display, mobile device display, remote control with display, or some other electronic display. The rendering 512 may belong to a web application and may include a landing page, checkout page, web page, website, web application, video on the web application, game on the web application, trailer, movie, advertisement, or Some other output from virtual worlds or networked applications. The rendering 512 may also be part of the display content, such as buttons, advertisements, banner advertisements, drop-down menus, and data elements on web-based applications or other parts of the display. In some embodiments, the webcam 530 may observe 532 the person to collect facial data. The face data may include information about action units, head pose, smile, frown, squint, lowered eyebrow, raised eyebrow, and attention. Alternatively, the eyes may be tracked to identify the portion of the rendering 512 on which the eyes are focused. For purposes of this disclosure and claims, the word "eye" may refer to one or both eyes of a single individual, or any combination of one or both eyes of multiple individuals in a group. Eyes of the person 520 may move while viewing 534 the rendering 512 . The images of the person 520 from the webcam 530 may be captured by a video capture unit 540 . In some embodiments, a video may be captured, while in other embodiments, a series of still images may be captured. The captured video or still images can be used in one or more analyses.

Analysis 550 of action units, posture, and mental state may be done using the captured image of the person 520 . These action units can be used to recognize smiles, frowns, and other facial indicators of mental state. These gestures, including head gestures, can indicate interest or curiosity. For example, a head gesture moving toward the electronic display 510 may indicate increased interest or a desire for clarification. Based on these captured images, analysis of physiological data can be performed. By analyzing these images, respiration, heart rate, heart rate variability, perspiration, temperature, and other physiological signs of mental state can be observed. So in various embodiments, a webcam is used to capture one or more of the facial data and the physiological data.

Figure 6 is a diagram representing physiological analysis. The system 600 can analyze the person 610 for whom data is collected. The person 610 may have a biosensor 612 attached to him or her in order to use the biosensor 612 to collect the mental state data. The biosensor 612 may be placed on the wrist, palm, hand, head or other parts of the body. In some embodiments, multiple biosensors may be placed at multiple locations on the body. The biosensor 612 may include detectors for physiological data, such as electrodermal activity, skin temperature, accelerometer readings, and the like. Other detectors for physiological data (such as heart rate, blood pressure, EKG, EEG, further brain waves) and other physiological detectors may also be included. The biosensor 612 may transmit collected information to a receiver 620 using wireless technology (eg, Wi-Fi, Bluetooth, 802.11, cellular, or other frequency bands). In other embodiments, the biosensor 612 can communicate with the receiver 620 through other methods (such as wired interface or optical interface). The receiver may provide the data to one or more components in the system 600 . In some embodiments, the biosensor 612 can record various physiological information in memory for later download and analysis. In some embodiments, downloading of the recorded physiological information can be accomplished through a USB port or other wired or wireless connection.

Mental state may be inferred based on physiological data, such as from the sensor 612 . Mental state may also be inferred based on facial expressions and head gestures observed by the webcam or a combination of data from the webcam and data from the sensor 612 . These mental states can be analyzed based on arousal and valence. Arousal can range from highly active (like when someone is anxious) to completely passive (like when someone is bored). Valence can range from very positive (such as when someone is happy) to very negative (such as when someone is angry). Physiological data may include electrodermal activity (EDA) or skin conductance or galvanic skin response (GSR), accelerometer readings, skin temperature, heart rate, heart rate variability, and other types of analysis in humans. It will be understood that, here and elsewhere in this document, physiological information may be obtained through biometric sensors 612 or through facial observation. Facial data may include facial movements and head poses for inferring mental states. In addition, this data may include information about hand posture or body language and body movements, such as visible fidgeting. In some embodiments, these movements may be captured by cameras or by sensor readings. Facial data may include tilting the head sideways, leaning forward, smiling, frowning, and many other gestures or expressions.

Electrodermal activity may be collected in some embodiments, and may be collected continuously, every second, four times per second, eight times per second, 32 times per second, or at some other periodicity. This electrodermal activity can be recorded. The recording can be to a disk, tape, onto flash memory, into a computer system, or streamed to a server. This electrodermal activity can be analyzed 630 to indicate arousal, agitation, boredom, or other mental states based on changes in skin conductance. Skin temperature can be collected and recorded periodically. The skin temperature may be analyzed 632 and may indicate arousal, agitation, boredom, or other mental states based on changes in skin temperature. This heart rate can be collected and recorded. The heart rate can be analyzed 634 and a high heart rate can indicate agitation, arousal or other mental state. Accelerometer data can be collected and indicate one, two or three dimensions of motion. The accelerometer data may be recorded. This accelerometer data can be used to create an actigraph showing an individual's activity level over time. The accelerometer data may be analyzed 636 and may indicate a sleep pattern, a highly active state, a listless state, or other states based on the accelerometer data. Various data collected by the biometric sensor 612 can be used along with facial data captured by the webcam.

Figure 7 is a diagram of cardiac related sensing. The system 700 can observe a person 710, the system can include a heart rate sensor 720, a certain type of biosensor. This observation can be via a contact sensor or via video analysis, which enables the capture of heart rate information or other non-contact sensing. In some embodiments, the physiological data is captured using a webcam. In some embodiments, the physiological data is used to determine locomotor activity, and in some embodiments the locomotor activity may be one of the group consisting of heart rate, respiration, and heart rate variability. Other embodiments may determine other spontaneous activity, such as pupil dilation or other spontaneous activity. The heart rate can be recorded 730 to a disk, tape, onto flash memory, into a computer system, or streamed to a server. The heart rate and heart rate variability may be analyzed 740 . An elevated heart rate can indicate agitation, nervousness, or other mental states. A decreased heart rate can indicate calmness, boredom, or other mental states. Levels of heart rate variability may be correlated with fitness, calmness, stress, or age. This heart rate variability can be used to help infer mental state. High heart rate variability can indicate good health and a lack of stress. Low heart rate variability can indicate high levels of stress. Thus, physiological data may include one or more of electrodermal activity, heart rate, heart rate variability, skin temperature, and respiration.

Figure 8 is a graphical representation of mental state analysis. A window 800 may be shown that includes, for example, a rendering of the networked application 810 with associated mental state information. The rendering in the example shown is a video but in other embodiments could be any other kind of rendering. A user may be able to select from multiple renderings using various buttons and/or labels, such as select video 1 button 820 , select video 2 button 822 , select video 3 button 824 , and select video 4 button 826 . Various embodiments may have many options available to the user, and some may be any type of rendering rather than video. A set of thumbnail images for the selected rendering (including Thumbnail 1830 , Thumbnail 2 832 , through Thumbnail N 836 in the example shown) may be shown with a timeline 838 below the rendering. Some embodiments may not include thumbnails or have a single thumbnail associated with the rendering, and various embodiments may have thumbnails of equal length, while other embodiments may have thumbnails of different lengths. In some embodiments, the start and/or end of the thumbnails may be determined by an editorial cut of the rendered video, while other embodiments may determine the start and/or end of the thumbnails based on changes in the captured mental state associated with the rendering. start and/or end. In an embodiment, a thumbnail image of the person whose mental state was analyzed may be shown.

Some embodiments may include the ability for a user to select a particular type of mental state information for display using various buttons or other selection methods. In the example shown, the smile mental state is shown when the user may have previously selected the smile button 840 . In various embodiments, other types of mental state information that may be selectable by the user may include lower eyebrow button 842, raised eyebrow button 844, attention button 846, valence score button 848, or other types of mental state information, according to embodiments. . The displayed mental state information may be based on physiological data, facial data, and actigraphy data. An overview button 849 may possibly be provided to allow the user to show graphs of multiple types of mental state information at the same time.

Because the smile option 840 has been selected in the example shown, a smile graph 850 may be shown against a baseline 852 showing aggregated smile mental state information for multiple individuals from which the mental state data was collected For rendering 810's. Male smile graph 854 and female smile graph 856 may be shown so that the visual representation presents aggregated mental state information based on demographics. Various demographic-based graphs may be indicated using various line styles as shown, or may be indicated using color or other distinguishing methods. Slide bar 858 may allow the user to select a particular time of the timeline and show the value of the selected mental state at that particular time. The slider can show the same line style or color as the population whose value is shown.

In some embodiments, demographic buttons 860 may be used to select various types of demographic-based mental state information. Such demographics may include gender, age, race, income level, or any other type of demographic, including dividing respondents into those with higher responses and those with lower responses. A legend 862 may be displayed showing the various population groups, the line style or color for each population group, the percentage of total respondents and or the absolute number of respondents for each group, and/or other information about the population groups. Psychological status information can be aggregated according to selected population types.

FIG. 9 is an illustration of a web page selected for sharing. Rendering 900 from a networked application can present an individual with an option to collect mental state. Flash ^™ may be used in some embodiments to present and/or request permission. Various embodiments may use different languages to request the individual's permission. In the illustrated embodiment, the individual is presented with text 910 representing the individual's permission to record facial expressions for the web-connected application. The video can be shown 920 to the individual. The video 920 may be video from the individual's webcam, content the individual will react to, a message requesting the individual's permission, or any other video. Some embodiments may include no video but only text or both text and images. The individual can respond to the invitation by clicking one of at least two buttons. If the individual does not want to be videotaped and have their mental state information shared, the individual can click the "no thanks" button 930 and no mental state information will be captured for the individual. If the individual would like to be videotaped and share their mental state information, the individual may click on the "Sure" button 940 to initiate the capture of their mental state information. Various embodiments may use buttons in other languages and some embodiments may include more than 2 options, such as including an option to share mental state information only with a specific group of people, capture facial data but not share the mental state information, Until the individual has reviewed the mental state information or other various restrictions on the mental state information. So sharing the mental state information may include choosing, by the individual, to share the mental state information.

FIG. 10 is an example social networking page content 1000 . The exact content and formatting may vary between the various social networks, but may be useful for various social networks (including but not limited to a blog site, Facebook ^™ , LinkedIn ^™ , MySpace ^™ , Twitter ^™ , Google+ ^™ , or any other social networks) format similar content. A social networking page for a particular social network may include one or more of the components shown in the social networking page content 1000, but may also include various other components instead of or in addition to the ones shown. The social networking content 1000 may include a title 1010, which may identify the social network and may include various tabs or buttons for navigating the social networking site, such as the "Home,""Profile," and "Friends" tabs shown . The social networking content 1000 may also include a profile photo 1020 of the individual who owns the social networking content 1000 . Various embodiments may include a friend list 1030 showing the individual's contacts on the particular social network. Some embodiments may include a comment component 1040 to show posts from the individual, friend, or other party.

The social networking content 1000 can include a state of mind field 1050 . The mental state information area 1050 may allow posting of mental state information to social network webpages. Depending on the embodiment, it may include mental state information that has been shared by the individual or may include mental state information that has been captured but not shared. In at least one embodiment, the individual may be presented with a mental state graph 1052 showing their mental state information while viewing a networked application, such as the graph of FIG. 2 . If the information has not been shared on the social network, a share button 1054 may be included in some embodiments. If the individual clicks on the share button 1054, mental state information (such as the mental state graph 1052 or various summaries of the mental state information) can be shared on the social network. Depending on the embodiment and the individual's choice, the mental state information may be shared with a person, a group or a subgroup of contacts or friends, another group defined by the social network, or may be open to anyone. The photo 1020 or another image shown on the social network can be updated with an image of the individual who shared the mental state information, such as a smiling photo, if the mental state information is happy. In some cases, the image of the individual is from a peak time of mental state activity. In some embodiments, the photos 1020 area or some other area of the social networking content 1000 may allow video and the images include video of the individual's reactions or represent the mental state information. If the shared mental state information is related to a web-connected application, forwarding the reference to the web-connected application as part of the sharing of the mental state information may be done and may include a URL and a timestamp that may indicate at a specific point in the video. Other embodiments may include a profile image from the web application or a profile video from the web application. Reposting or sharing of various mental state information and related items can be done on a single social network, or some items can be reposted on one social network while other items are reposted on another social network. In some embodiments, the sharing is part of a rating system for the networked application, such as aggregating mental state information from multiple users to automatically generate ratings for videos.

Some embodiments may include a mental state score 1056 . In some embodiments, the mental state data is collected over a period of time and the mental state information shared is a reflection of the individual's mood in the mental state score 1056 . The mental state score may be a number, a sliding scale, a colored scale, various icons or images representing mood, or any other type of representation. In some embodiments, the mental state score 1056 may mimic the popular "mood rings" of the 1970's. A variety of moods can be represented, including but not limited to frustration, confusion, disappointment, hesitation, cognitive overload, focus, busyness, attention, boredom, exploration, confidence, trust, joy, and satisfaction.

Some embodiments may include a field 1058 for aggregated mood states of friends. This section may include aggregated moods of those friends shown in the friends section 1030 who have chosen to share their state of mind information. Other embodiments may include an aggregated mental state of friends who have viewed the same networked application as the individual, and may allow the individual to compare their mental state information in the mental state graph 1052 with that of their friends. 1058 for comparison. Other embodiments may show various aggregations of different groups.

FIG. 11 is a system diagram 1100 for sharing on social networks or a system for sharing mental states. The Internet 1110, an intranet, or other computer network can be used for communication between the various computers. The client computer 1120 has a memory 1126 for storing instructions and one or more processors 1124 attached to the memory 1126, where the one or more processors 1124 can execute the instructions. The client computer 1120 may also have an Internet connection to communicate mental state information 1121, and a display 1122 that may present various renderings to the user. The client computer 1120 may be able to collect mental state data from an individual or individuals as they interact with a rendering. In some embodiments, there may be multiple client computers 1120, each of which may collect mental state data from a person or people as they interact with a rendering. In other embodiments, the client computer 1120 may receive mental state data from individuals as they interact with a rendering. The client computer 1120 may receive an instruction from the individual to opt-in to share the mental state information. Once the mental state data has been collected, if permission is received, the client computer may upload information to server 1130 based on the mental state data from the plurality of persons interacting with the rendering. The client computer 1120 may communicate with the server 1130 through the Internet 1110, some other computer network, or by other methods suitable for communication between two computers. In some embodiments, the functions of the server 1130 can be implemented in the client computer.

The server 1130 may have an Internet connection for receiving mental states or collected mental state information 1131, and have a memory 1134 storing instructions and one or more processors 1132 attached to the memory 1134 to execute the instructions . The server 1130 can receive mental state information from individuals as they interact with a rendering from the client computer 1120 or computer, and can analyze the mental state data to generate mental state information. The server 1130 can also aggregate mental state information about the plurality of persons interacting with the rendering. The server 1130 may also associate the aggregated mental state information with the rendering, and also with the set of criteria for the environment being measured. In some embodiments, the server 1130 may also allow users to view and evaluate mental state information associated with the rendering, but in other embodiments, the server 1130 may send the aggregated mental state information 1141 to a social network 1140 To share, distribute the mental state information over a computer network. This can be done to share the mental state information on a social network. In some embodiments, the social network 1140 can run on the server 1130 .

Each of the methods described above can be executed on one or more processors on one or more computer systems. Embodiments may include various forms of distributed computing, client/server computing, and cloud-based computing. Furthermore, it is to be understood that each flowchart, depicted step, and block in this disclosure is provided for purposes of illustration and description only. These steps may be modified, omitted, or reordered and other steps may be added without departing from the scope of the present disclosure. Furthermore, each step may contain one or more sub-steps. While the foregoing drawings and descriptions present functional aspects of the disclosed systems, no particular arrangement of software and/or hardware for implementing these functional aspects should be inferred from these descriptions unless explicitly stated or otherwise taken from context It is very clear. All such arrangements of software and/or hardware will fall within the scope of this disclosure.

The block and flowchart illustrations depict methods, apparatuses, systems, and computer program products. Each element of the block diagrams and flowchart illustrations, and each corresponding combination of elements in these block diagrams and flowchart illustrations, illustrates one of these methods, apparatus, systems, computer program products, and/or computer-implemented methods A function, step, or set of steps. Any and all such functions may be implemented by computer program instructions, by special purpose hardware-based computer systems, by a combination of special purpose hardware and computer instructions, by a combination of general purpose hardware and computer instructions, and so on. Any and all of these may be generically referred to herein as a "circuit," "module," or "system."

A programmable device for executing any of the above-mentioned computer program products or computer-implemented methods may include one or more microprocessors, microcontrollers, embedded microcontrollers, programmable digital signal processors, programmable devices, programmable Programmable Gate Arrays, Programmable Array Logic, Memory Devices, ASICs, etc. Each can be suitably used or configured to process computer program instructions, execute computer logic, store computer data, and the like.

It will be understood that a computer may include a computer program product from a computer readable storage medium, and that this medium may be internal or external, removable and replaceable, or fixed. Additionally, a computer may include a basic input/output system (BIOS), firmware, operating system, database, etc., which may include, interface with, or support the software and hardware described herein.

Embodiments of the invention are not limited to conventional computer programs or applications running on programmable devices. It is believed that, for example, embodiments of the presently claimed invention may include optical computers, quantum computers, analog computers, and the like. A computer program can be loaded onto a computer to create a specific machine that can perform any and all of the functions depicted. This particular machine provides a means for performing any and all of the functions depicted.

Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable medium for storage. A computer readable storage medium may be electronic, magnetic, optical, electromagnetic, infrared semiconductor, or any suitable combination of the foregoing. Further examples of computer readable storage media may include an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read only memory (ROM) , an erasable programmable read-only memory (EPROM, flash memory, MRAM, FeRAM, or phase change memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any appropriate combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that may contain or store programs for use by or in connection with an instruction execution system, device, or apparatus.

It will be appreciated that computer program instructions may comprise computer executable code. Various languages for expressing computer program instructions may include, but are not limited to, C, C++, Java, JavaScript ^™ , ActionScript ^™ , assembly language, Lisp, Perl, Tel, Python, Ruby, hardware description languages, database programming languages, functional Programming languages, imperative programming languages, and more. In an embodiment, computer program instructions may be stored, compiled or interpreted to run on a computer, programmable data processing apparatus, processor or heterogeneous combination of processor architectures, and the like. Without limitation, embodiments of the invention may take the form of web-based computer software, including client/server software, software-as-a-service, peer-to-peer software, and the like.

In an embodiment, a computer may enable the execution of computer program instructions, including multiple programs or threads. The multiple programs or threads can be processed nearly simultaneously to increase utilization of the processor and facilitate substantially simultaneous functionality. By implementation, any and all methods, program code, program instructions, etc. described herein may be implemented in one or more threads. Each thread may spawn other threads, which itself may have a priority associated with it. In some embodiments, the computer may process the threads based on priority or other order.

Unless expressly stated or otherwise clear from the context, the verbs "execute" and "process" may be used interchangeably to mean execute, process, interpret, compile, assemble, link, load, or combination. Thus, an embodiment of executing or processing computer program instructions, computer-executable code, etc. may act upon the instructions or code in any and all methods described. Additionally, the method steps shown are intended to encompass any suitable method that causes one or more parties or entities to perform the steps. The parties performing a step or a part of a step need not be located within a particular geographic location or national borders. For example, if an entity located in the United States causes a method step, or a portion thereof, to be performed outside the United States, the method is considered to be performed in the United States because the entity caused the step to be performed.

While the invention has been disclosed in connection with the preferred embodiment shown and described in detail, various modifications and improvements thereto will become apparent to those skilled in the art. Accordingly, the spirit and scope of the present invention are not limited by the above examples, but should be understood in the broadest sense permitted by law.

Claims (99)

1. computer-implemented method of be used for linking up mental status, this method comprises: collect people's mental status data one by one;

Analyze these mental status data to produce mental status information; And

Share this mental status information at a social networks.

2. the method for claim 1 further comprises by this personal selection and shares this mental status information.

3. method according to claim 2 further is included in this selection and presents this mental status information to this individual before.

4. the method for claim 1, wherein these mental status data are collected in a period of time, and this mental status information of sharing is the reflection to this individual mood.

5. method as claimed in claim 4, wherein this mood comprises in the group down one, this group comprises: dejected, puzzled, disappointed, know which way to go, cognitive overload, be absorbed in, have much to do, attention, boring, exploration, confidence, trust, happiness and satisfaction.

6. the method for claim 1, wherein this is shared and comprises mental status information is published to a social networks webpage.

7. the method for claim 1 further comprises this mental status information is uploaded to a server.

8. the method for claim 1 further is included in this mental status information of issue on the computer network.

9. the method for claim 1, wherein these mental status data comprise in the group down one, this group comprises: physiological data, face data, and activity inventory instrument data.

10. method as claimed in claim 9, one of them web camera are used to catch in this face data and this physiological data one or multinomial.

11. method as claimed in claim 9, wherein this face data comprises about one or multinomial information in the following group, and this group comprises countenance, motor unit, head pose, smiles, frowns, blink, low eyebrow, lift eyebrow, and pay close attention to.

12. method as claimed in claim 9, wherein this physiological data comprise electrodermal activity, heart rate, heart rate variability, skin temperature, and breathe in one or multinomial.

13. the method for claim 1 further comprises based on this collected mental status data-speculative mental status.

14. method as claimed in claim 13 further is included in seemingly mental status of recognition category in this social networks.

15. method according to claim 13, wherein these mental statuss comprise in the following group one, and this group comprises: dejected, puzzled, disappointed, know which way to go, cognitive overload, be absorbed in, have much to do, attention, boring, exploration, confidence, trust, happiness and satisfaction.

16. method according to claim 1 further comprises and transmits this individual image with this mental status information of sharing.

17. method according to claim 16, this image that wherein should the individual is from the time to peak of mental status activity.

18. method as claimed in claim 16, wherein this image comprises a video.

19. the method for claim 1 comprises that further the issue with this mental status information is limited in the subclass of this social networks.

20. the method for claim 1 further is included in and shares the mental status information that gathers on this social networks.

21. method according to claim 1, wherein these mental status data are collected when this individual and a networked application programs are mutual.

22. method according to claim 21, wherein this networked application programs is following in the group, and this group comprises: a video on login page, page of checking out, webpage, website, this networked application programs, a recreation on this networked application programs, trailer, film, advertisement, reach a virtual world.

23. method according to claim 21 further comprises being forwarded to this networked application programs with quoting, as this part of sharing of this mental status information.

24. method as claimed in claim 23, wherein this is quoted and comprises a URL and a timestamp.

25. method as claimed in claim 23, wherein this forwarding comprises a source map picture from this networked application programs.

26. method as claimed in claim 23, wherein this forwarding comprises a data video from this networked application programs.

27. method according to claim 21, wherein this to share be a part for the rating system of this networked application programs.

28. method according to claim 1, wherein these mental status data are to use a biosensor to collect.

29. a computer program of realizing at the computer-readable medium that is used for the communication mental status, this computer program comprises:

Be used for collecting the code of people's mental status data one by one;

Be used for analyzing these mental status data to produce the code of mental status information; And

Be used for sharing at a social networks code of this mental status information.

30. computer program as claimed in claim 29 further comprises for the code of being shared this mental status information by this personal selection.

31. computer program according to claim 30 further comprises for the code that presented this mental status information before this selection to this individual.

32. computer program as claimed in claim 29, wherein these mental status data are collected in a period of time, and this mental status information of sharing is the reflection to this individual mood.

33. computer program as claimed in claim 32, wherein this mood comprises in the following group one, and this group comprises: dejected, puzzled, disappointed, know which way to go, cognitive overload, be absorbed in, have much to do, attention, boring, exploration, confidence, trust, happiness and satisfaction.

34. computer program as claimed in claim 29, wherein this is shared and comprises mental status information is published on the social networks webpage.

35. computer program as claimed in claim 29 further comprises for the code that this mental status information is uploaded to a server.

36. computer program as claimed in claim 29 further comprises for the code this mental status information of computer network issue.

37. computer program as claimed in claim 29, wherein these mental status data comprise in the following group one, and this group comprises: physiological data, face data, and activity inventory instrument data.

38. computer program as claimed in claim 37, one of them web camera are used to catch in this face data and this physiological data one or multinomial.

39. computer program as claimed in claim 37, wherein this face data comprises about one or multinomial information in the following group, and this group comprises countenance, motor unit, head pose, smiles, frowns, blink, low eyebrow, lift eyebrow, and pay close attention to.

40. computer program as claimed in claim 37, wherein this physiological data comprise electrodermal activity, heart rate, heart rate variability, skin temperature, and breathe in one or multinomial.

41. computer program as claimed in claim 29 further comprises for the code based on this collected mental status data-speculative mental status.

42. computer program as claimed in claim 41 further comprises for the code of recognition category in this social networks like mental status.

43. according to the described computer program of claim 41, wherein these mental statuss comprise in the following group one, and this group comprises: dejected, puzzled, disappointed, know which way to go, cognitive overload, be absorbed in, have much to do, attention, boring, exploration, confidence, trust, happiness and satisfaction.

44. computer program according to claim 29 further comprises the code that has this individual image of this mental status information of sharing for transmission.

45. according to the described computer program of claim 44, this image that wherein should the individual is from the time to peak of mental status activity.

46. computer program as claimed in claim 44, wherein this image comprises a video.

47. computer program as claimed in claim 29 further comprises the code that is limited in the subclass of this social networks for the issue with this mental status information.

48. computer program as claimed in claim 29 further comprises for the code of sharing the mental status information that gathers at this social networks.

49. computer program according to claim 29, wherein these mental status data are collected when this individual and a networked application programs are mutual.

50. according to the described computer program of claim 49, wherein this networked application programs is following in the group, and this group comprises: a video on login page, page of checking out, webpage, website, this networked application programs, a recreation on this networked application programs, trailer, film, advertisement, reach a virtual world.

51. according to the described computer program of claim 49, further comprise for quoting being forwarded to this networked application programs as the code of this part of sharing of this mental status information.

52. computer program as claimed in claim 51, wherein this is quoted and comprises a URL and a timestamp.

53. computer program as claimed in claim 51, wherein this forwarding comprises a source map picture from this networked application programs.

54. computer program as claimed in claim 51, wherein this forwarding comprises a data video from this networked application programs.

55. according to the described computer program of claim 49, wherein this to share be a part for the rating system of this networked application programs.

56. computer program according to claim 29, wherein these mental status data are to use a biosensor to collect.

57. one kind is used for sharing the system of mental status, this system comprises:

A memorizer that is used for store instruction;

Be attached to the one or more processors on this memorizer, wherein these one or more processors are configured to:

Collect people's mental status data one by one;

Analyze these mental status data to produce mental status information;

Receive an instruction from this individual, to select to share this mental status information; And

Share this mental status information at a social networks.

58. system as claimed in claim 57, wherein these one or more processors are further configured into by this personal selection and share this mental status information.

59. according to the described system of claim 58, wherein these one or more processors were further configured into before selecting and present this mental status information to this individual.

60. system as claimed in claim 57, wherein these mental status data are collected in a period of time, and this mental status information of sharing is the reflection to this individual mood.

61. system as claimed in claim 60, wherein this mood comprises in the following group one, and this group comprises: dejected, puzzled, disappointed, know which way to go, cognitive overload, be absorbed in, have much to do, attention, boring, exploration, confidence, trust, happiness and satisfaction.

62. system as claimed in claim 57, wherein this is shared and comprises mental status information is published on the social networks webpage.

63. system as claimed in claim 57, wherein these one or more processors are further configured into this mental status information are uploaded to a server.

64. system as claimed in claim 57, wherein these one or more processors are further configured into this mental status information of computer network issue.

65. system as claimed in claim 57, wherein these mental status data comprise in the following group one, and this group comprises: physiological data, face data, and activity inventory instrument data.

66. as the described system of claim 65, wherein this face data comprises about one or multinomial information in the following group, this group comprises countenance, motor unit, head pose, smiles, frowns, blink, low eyebrow, lift eyebrow, and pay close attention to.

67. as the described system of claim 65, wherein this physiological data comprise electrodermal activity, heart rate, heart rate variability, skin temperature, and breathe in one or multinomial.

68. as the described system of claim 65, one of them web camera is used to catch in this face data and this physiological data one or multinomial.

69. system as claimed in claim 57, wherein these one or more processors are further configured into based on this collected mental status data-speculative mental status.

70. as the described system of claim 69, wherein these one or more processors are further configured into seemingly mental status of recognition category in this social networks.

71. according to the described system of claim 69, wherein these mental statuss comprise in the following group one, this group comprises: dejected, puzzled, disappointed, know which way to go, cognitive overload, be absorbed in, have much to do, attention, boring, exploration, confidence, trust, happiness and satisfaction.

72. according to the described system of claim 57, wherein these one or more processors are further configured into this individual image that transmission has this mental status information of sharing.

73. according to the described system of claim 72, this image that wherein should the individual is from the time to peak of mental status activity.

74. as the described system of claim 72, wherein this image comprises a video.

75. system as claimed in claim 57, wherein these one or more processors are further configured into a subclass that the issue of this mental status information is limited in this social networks.

76. system as claimed in claim 57, wherein these one or more processors are further configured at this social networks and share the mental status information that gathers.

77. according to the described system of claim 57, wherein these mental status data are collected when this individual and a networked application programs are mutual.

78. according to the described system of claim 77, wherein this networked application programs is following in the group, and this group comprises: a video on login page, page of checking out, webpage, website, this networked application programs, a recreation on this networked application programs, trailer, film, advertisement, reach a virtual world.

79. according to the described system of claim 77, wherein these one or more processors are further configured into and are forwarded to this networked application programs with quoting, as this part of sharing of this mental status information.

80. as the described system of claim 79, wherein this is quoted and comprises a URL and a timestamp.

81. as the described system of claim 79, wherein this forwarding comprises a source map picture from this networked application programs.

82. as the described system of claim 79, wherein this forwarding comprises a data video from this networked application programs.

83. according to the described system of claim 77, wherein this to share be a part for the rating system of this networked application programs.

84. according to the described system of claim 57, wherein these mental status data are to use a biosensor to collect.

85. one kind is used for sharing the computer-implemented method of mental status, this method comprises:

Receive mental status information based on the mental status data from people one by one;

Infer the mental status that this is individual based on this received mental status information; And

Share these mental statuss of inferring at a social networks.

86. as the described method of claim 85, further comprise by this individual receiving the selection of sharing this mental status information.

87. as the described method of claim 85, wherein these mental status data are collected in a period of time, and this mental status information of sharing is the reflection to this individual mood.

88. as the described method of claim 87, wherein this mood comprises in the following group one, this group comprises: dejected, puzzled, disappointed, know which way to go, cognitive overload, be absorbed in, have much to do, attention, boring, exploration, confidence, trust, happiness and satisfaction.

89. as the described method of claim 85, wherein this is shared and comprises mental status information is published on the social networks webpage.

90. as the described method of claim 85, wherein these mental status data comprise in the following group one, this group comprises: physiological data, face data, and activity inventory instrument data.

91. as the described method of claim 90, one of them web camera is used to catch in this face data and this physiological data one or multinomial.

92. as the described method of claim 91, wherein this face data comprises about one or multinomial information in the following group, this group comprises countenance, motor unit, head pose, smiles, frowns, blink, low eyebrow, lift eyebrow, and pay close attention to.

93. as the described method of claim 91, wherein this physiological data comprise electrodermal activity, heart rate, heart rate variability, skin temperature, and breathe in one or multinomial.

94. as the described method of claim 85, wherein this supposition of these mental statuss is based on these mental status data of collecting from this individual.

95. as the described method of claim 94, further be included in seemingly mental status of recognition category in this social networks.

96. as the described method of claim 85, comprise that further the issue with this mental status information is limited in the subclass of this social networks.

97. as the described method of claim 85, further be included in and share the mental status information that gathers on this social networks.

98. 5 described methods further comprise being forwarded to a networked application programs with quoting, as this part of sharing of this mental status information according to Claim 8.

99. 5 described methods according to Claim 8, wherein these mental status data are to use a biosensor to collect.

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